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This web site is building a set of free materials, lectures, bookand assignments to help studentslearn how to program in Python.You can take this course and receive a certificate at: If you log in to this siteyou have joined a free, globalopen and online course. You have a grade book, autograded assignments, discussion forums, and can earnbadges for your efforts.We take your privacy seriously on this site, you can review ourPrivacy Policy for more details.If you want to use these materialsin your own classes you can download or link to the artifacts on this site,export the course material as anIMS Common Cartridge®, or apply foran IMS Learning Tools Interoperability® (LTI®)key and secret to launch the autograders from your LMS.The code for this site including the autograders, slides, and course content is all available onGitHub. That means you could make your owncopy of the course site, publish it and remix it any way you like. Even more exciting, you could translatethe entire site (course) into your own language and publish it. I have providedsome instructions on how to translate this course in my GitHub repository.This site uses Tsugiframework to embed a learning management system into this site andprovide the autograders.If you are interested in collaboratingto build these kinds of sites for yourself, please see thetsugi.org website andorcontact me. And yes, Dr. Chuck actually has a race car - it is called theSakaiCar.He races in a series called24 Hours of Lemons. The goal of this book is to provide an Informatics-oriented introduction to programming. The primary difference between a computer science approach and the Informatics approach taken in this book is a greater focus on using Python to solve data analysis problems common in the world of Informatics. The sample code and data files for the book is here: Code Samples.Other courses web sites using this bookBook translations:Greek German Russian Russian versions of the slides fromVioletta Fomkina. Korean (commercial translation)데이터를 다루며 배우는 파이썬 Chinese - In progress If you are insterested in starting a translation of the book, I have someinstructions forgetting started. Chapters 2-10 are heavily adapted from the open book titled: Think Python: How to Think like a Computer Scientist by Allen B. Downeyand Jeff Elkner.The Python 2 version of the book is still available. Copyright Creative Commons Attribution 3.0 - Charles R. Severance Learn more about reviews.Reviewed by Youyou Tao, Assistant Professor, Loyola Marymount University on 22522Ive taught programming for about four years. The topics that I covered in my courses include fundamental concepts and topics in Python programming, web scraping, and Python for data analytics. Ive struggled a long time to find a textbook that...read moreReviewed by Maira Monteiro, Assistant Professor, Seattle Pacific University on 1322This is a great introductory textbook addressing the main aspects of Python. Topics are covered with up-to-the-point discussions and meaningful examples. It is a powerful resource for beginners in the topic, meaningfully supporting the Open...read moreReviewed by Micheline Al Harrack, Continuing Instructor, Marymount University on 111921This text can be broken down into two parts: the first ten chapters constitute a comprehensive introduction to basic Python concepts while the remaining chapters explore topics related to data acquisition and visualization (web, databases, SQL)....read moreReviewed by Mya T. Bowen, Assistant Professor, Roxbury Community College on 61721The text covers all areas and ideas of the subject appropriately and provides an effective glossary at the end of every chapter.read moreReviewed by Shahab Hussain, Adjunct Professor, North Shore Community College on 6221This book presents majority of the Python Programming critical areas and explains with useful examples.read moreReviewed by Syeda Ferdous Begum, Professor, Middlesex Community College on 41421, updated 42021This book great for beginner programmer who does not know anything about programming. This text can be used in the computer science and information technology field. Even though it is targeted towards beginners, it contains advanced topics but...read moreReviewed by Sankardas Roy, Assistant Professor, Bowling Green State University on 13121As the title suggests, the intended audience of this book is everybody who wants to explore Python for data analysis work. The book does cover the basics of Python programming, giving sufficient amount of subject details for a new programmer....read moreReviewed by Kuuipo Walsh, Director, Oregon State University on 82820Dr. Charles R. Severances book introduces the fundamentals of Python programming in Chapters 1-10, without diving deeply into object-oriented programming. These chapters focus on code examples manipulating text and text files. Given the title, it...read moreReviewed by Joe Paris, Faculty, Linn-Benton Community College on 7220This book is an approachable introduction to both Python the language and its application to information science -- namely retrieving, cleaning, and storing data for later analysis. Chapters two through ten are based heavily on Allen Downey and...read moreReviewed by Matt Bailey, Associate Professor, Bucknell University on 22519The book is a comprehensive and approachable introduction to Python. The first nine chapters are terse, but comprehensive introduction to Python. Given the title, I had expected some discussion of the pandas Python package. It is more geared...read moreReviewed by Giancarlo Schrementi, Instructor, Hollins University on 52118This book is a remix of the excellent Think Python book by Allen Downey. The book keeps the clarity of the original while including examples skewed towards data applications, particularly text processing. The remix adds chapters on regular...read more
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